1. Field
The exemplary embodiments generally relates to an order fulfillment system for use in supply chains.
2. Brief Description of the Related Developments
An order-fulfillment system for use in supply chains, for example in retail supply chains, may fulfill orders for individual product units, referred to herein as “eaches” (also called “pieces”, “articles”, “items” or, generally, any articles available for purchase in retail as a purchase unit, etc.), which are typically packaged and shipped by the manufacturer in containers known as “cases”. The “each” as used herein for convenience purposes, may be considered the most granular unit of handling in retail supply chains. Conventional operations to fulfill orders for eaches (usually referred to as “each-picking” or “piece-picking”) are generally labor-intensive because they generally apply man-to-goods processes that are not highly automated.
The broad field of each-picking within retail supply chains can be viewed as comprising two distinct application domains: (1) store-replenishment applications, in which the orders are placed by retail stores and the picked caches are delivered to those stores and placed on shelves to be selected and purchased by customers in the stores, and (2) direct-to-consumer applications, in which the orders are placed by end users and the picked caches are delivered directly to those end users. In both domains, an order consists of a series of “order-lines”, each order-line specifying a particular product (or “stock keeping unit” or simply “SKU”) and a quantity (number of caches) of that product to be delivered. However there are several important differences in the operational metrics of applications within these two domains. Store-replenishment applications typically have many fewer orders than direct-to-consumer applications (as there are many fewer stores than end users), but the average number of order-lines per order is much higher for store-replenishment orders than for typical direct-to-consumer order. Also, the average number of units per order line is far greater for store-replenishment orders than for direct-to-consumer orders (because stores are buying units to sell to many customers whereas consumers are buying for their individual use). And most importantly, the total number of order lines for a given SKU (order-lines per SKU), relative to total order lines to be filled during a given time period, is much higher in the store-replenishment domain than in the direct-to-consumer domain. This is because stores typically carry very similar assortments and order more SKUs in each order, making it much more likely that a given SKU will be included in a relatively high percentage of orders, whereas consumers have diverse tastes and preferences and are ordering fewer SKUs, making it more likely that a given SKU will be contained in a relatively low percentage of orders.
These last two metrics—units per order-line and order-lines per SKU—are factors in the design an each-picking system, and the differences in these metrics between the two domains typically results in very different system designs. It is an object of the disclosed embodiment to be highly cost-efficient and effective in both domains of each-picking, but to provide design flexibility that allows the configuration to be optimized for the application based on operational metrics. As a result, in different aspects of the disclosed embodiment, the system configuration may be one optimized for each domain as will be discussed further below.